The recent article by Larrosa et al.1 describes the use of a new predictive formula for glaucoma detection, especially in early glaucoma, using Cirrus optical coherence tomography (OCT) parameters. The authors combined in this predictive formula the parameters that resulted in the best areas under the receiver operating characteristic curves (AUC) from the retinal nerve fiber layer (RNFL), the retinal ganglion cell–inner plexiform layer (GCIPL), and the optic head nerve (OHN). We found the AUC of the calculator was better for glaucoma detection than the same parameters used in isolation. This formula obtained the quantitative probability of glaucoma (in percentage) and the qualitative probability: low (values between 0% and 30%), intermediate (30%–60%), and high glaucoma probability (>60%). The authors provided a Web page to download a spreadsheet file (Excel; Microsoft Corp., Redmond, WA, USA) with this formula.

Glaucoma evaluation using the Cirrus OCT has the limitation of false positives (FP) in the diagnostic color codes.2–3 In a previous paper that included 100 normal eyes, we found 39% of the eyes to be FP in the average RNFL, 11% in the GCIPL, and 11% in the OHN analysis using Cirrus.2 However, the FP incidence was lower in the Spectralis OCT, indicating that Spectralis OCT has better specificity than Cirrus OCT. We identified the axial length, the higher spherical equivalent myopic defect, the presence of peripapillary atrophy, and the tilted and/or torted optic disc as factors significantly associated with an abnormal classification in the color code provided by both Cirrus or Spectralis OCT.2 Abnormal OCT diagnostic classification should be interpreted with caution, especially in eyes where these factors are associated with FP. To understand if the predictive formula from Larrosa et al.1 can decrease the percentage of FP in normal eyes, we used this formula to analyze the same sample of 100 eyes, which found 39% to be FP using Cirrus OCT. The application of this formula obtains a low glaucoma probability in the 100 eyes, and finds no cases with intermediate or high glaucoma probability. The main quantitative probability is 3.06% (SD 4.75) in the FP cases and the 1.18% (SD 1.69) in eyes without FP (P = 0.001, Mann-Whitney test). This significant difference can be explained because color code forms part of the predictive formula. The majority of cases with FP have a quantitative glaucoma probability of less than 10%. Only one case has a quantitative probability of 24.3% in an eye with a yellow color code in the GCIPL and a red color code in the cup-to-disc ratio average color. These results suggest that the Larrosa et al.1 quantitative predictive formula could be useful in cases with red color code in patients with normal visual field and suspicion of FP. In cases where FP is suspected, currently it is recommended that the patient undergoes another OCT device analysis such as Spectralis. However, a second OCT is not always available and when it is, it is time-consuming. In contrast, the analysis of the glaucoma probability using the Larrosa et al.1 formula is efficient in that it only takes 1 minute to apply. According to our results, we recommend that this formula be applied in isolated Cirrus OCT with altered color code to detect if it is glaucoma or a FP.